New research on the neural system of language

Neuroscientists have long known that particular areas of the brain are responsible for the comprehension and production of language. But new research points to the criticality of pathways between these areas for various components of language.

From a Science Daily article summarizing the research:

Two brain areas called Broca’s region and Wernicke’s region serve as the main computing hubs underlying language processing, with dense bundles of nerve fibers linking the two, much like fiber optic cables connecting computer servers. But while it was known that Broca’s and Wernicke’s region are connected by upper and a lower white matter pathways, most research had focused on the nerve cells clustered inside the two language-processing regions themselves.

MRI image shows Brocca's (yellow) and Wernicke's (purple) regions, connected by critical neural pathways. (Image credit: Stephen Wilson, Science Daily)

University of Arizona Professor of Speech and Hearing Stephen Wilson was one of the lead researchers:

If you have damage to the lower pathway, you have damage to the lexicon and semantics. You forget the name of things, you forget the meaning of words. But surprisingly, you’re extremely good at constructing sentences.

With damage to the upper pathway, the opposite is true; patients name things quite well, they know the words, they can understand them, they can remember them, but when it comes to figuring out the meaning of a complex sentence, they are going to fail.

Professor Wilson collaborated on the research with colleagues from the University of California at San Francisco and the Scientific Institute and University Hospital San Raffaele in Milan, Italy. The research was published in the journal Neuron.

Studying Japanese yields clues for kids with dyslexia learning English

The Wall Street Journal reports on recent research into the use of character-based languages such as the Japanese language kanji.

Learners with dyslexia struggle with the association between letters and sounds in English (a language in which words are comprised of groups of sounds that readers decode). However, character-based languages, where the characters represent complete words or ideas, are mastered through memorization, a skill that many students with dyslexia have mastered to compensate for their decoding struggles.

One study featured in the WSJ article looked at fMRI brain scans of dyslexic students and discovered that they use the same area of the brain to read English as do readers of kanji, a character-based Japanese language. This is different from the area of the brain used by typically developing English readers (and readers of kana, another Japanese language in which characters represent sounds instead of words or ideas).

As the article notes, we don’t cure dyslexia by teaching students in a character-based language. But it does offer some insight into how these kids’ brains are working differently and how teachers might be able to deliver reading-based content more effectively.

We have a link to a fantastic dyslexia study on our Web site. The study, performed at Stanford, is very consistent with the findings discussed in the WSJ article, as it supports the idea that students with dyslexia tend to make reading a more visual task, while typically developing readers integrate auditory processing as well.

 

Competing Memories

Does something like this ever happen to you?  From Yale psychologist Brice Kuhl, quoted in a NY Times article about memory:

“I park in a garage every day at work, and I park in a different space every day, depending on availability. And I very often walk to where I parked the day before. It’s not that I totally forgot where I parked, it’s just that I still remember yesterday’s spot.”

When the brain is cluttered with similar items (say a new password replacing an expired one, or a new phone number), we have difficulty recalling just one. Kuhl’s research (published in the Proceedings of the National Academy of Sciences) indicates that this difficulty is reflected in “more ambiguous” neural activation when engaged in competitive remembering as compared to “more robust” activation for non-competitive memories.

Moonwalking with Einstein

Last weekend’s NY Times Magazine featured an excerpt from journalist Joshua Foer’s new book Moonwalking with Einstein: The Art and Science of Remembering Everything. It’s the fascinating story of his quest to become the memory champion of the United States (add that to the list of things we didn’t know anything about).

As we’ve previously posted, there’s an important distinction between memory and memorization. Nonetheless, memorization techniques can give us clues about memory, particularly from an evolutionary standpoint. For example, Foer highlights a study that showed that expert memorizers have neither anatomically distinguishable brains nor above average levels of cognitive abilities. But what they do share is a higher level of activation in the area of the brain responsible for visual and spatial memory. Experts attribute this to the fact that our ancestors relied on visual spatial memory for survival (where’s the food? where are the predators?).

Foer’s journey to the title is interesting, at least in part because he really set out just to learn about memorization and ended up a champion. The Times article links to two resources for memorizing numbers and names. For more on Foer, check out this story by NPR’s All Things Considered.

TED Talk on the Linguistic Genius of Babies

In this great 10-minute lecture, Patricia Kuhl, co-director of the Institute for Brain and Learning Sciences at the University of Washington, shares her findings about how babies learn one language over another — by listening to the humans around them and “taking statistics” on the sounds they need to know.

Experiments and brain imaging show how 6-month-old babies use sophisticated reasoning to understand their world. Dr. Kuhl’s work has played a major role in demonstrating how early exposure to language alters the brain. It has implications for critical periods in development, for bilingual education and reading readiness, for developmental disabilities involving language, and for research on computer understanding of speech.

Brain vs. Mind

Several years ago, a colleague recommended M. Mitchel Waldrop’s book Complexity: The Emerging Science at the Edge of Order and Chaos. I’m not going to do justice to the, well, complexity, of complexity theory, but my two takeaways were that:

• Incredibly complex systems can emerge very quickly from very basic rules or parameters. Think of birds flying in formation, who encounter an obstacle like a sky scraper and can quickly re-assemble their formation on the other side, guided only by rules that govern their relationship to the bird in front of them.
• Laboratory experiments where scientists remove variables in order to get to a “core” phenomenon may be of little utility, since no physical process occurs in such isolation in nature.

Mentioned in Waldrop’s book is the Santa Fe Institute, a non-profit institute that supports complex systems research. From the Institute’s Web site:

Complex systems research attempts to uncover and understand the deep commonalities that link artificial, human, and natural systems. By their very nature, these problems transcend any particular field, for example, if we understand the fundamental principles of organization, we will gain insight into the functioning of cells in biology, firms in economics, and magnets in physics. This research relies on theories and tools from across the sciences. Part of the rise of the complex systems research agenda can be tied to the use of theoretical computation as a new way to explore such systems.

Legend has it that the founders of Scientific Learning (creators of the Fast ForWord programs), Drs. Michael Merzenich and Paula Tallal, met at the Santa Fe Institute. Merzenich, a neuroscientist, had been doing groundbreaking research into brain plasticity, while Tallal, a neuropsychologist, focused on language acquisition. Their combined work leveraged their expertise in both fields, and created a revolutionary program with a reach that far exceeds that of their individual research.

I don’t know if he would consider himself a complexity theorist, but an essay by Andy Clark, professor of logic and metaphysics in the School of Philosophy, Psychology, and Language Sciences at Edinburgh University, Scotland, evoked the kind of multi-dimensional and multi-disciplinary thinking that inspired the creation of Fast ForWord. Clark’s essay takes a shot at recent brain research (which sometimes appears to consist entirely of fMRI brain scans):

We are all familiar with the colorful “brain blob” pictures that show just where activity (indirectly measured by blood oxygenation level) is concentrated as we attempt to solve different kinds of puzzles: blobs here for thinking of nouns, there for thinking of verbs, over there for solving ethical puzzles of a certain class, and so on, ad blobum.

While supporting this kind of research (“Some of my best friends are neuroscientists and neuro-imagers” says Clark), he does ask an interesting question:

Is it possible that, sometimes at least, some of the activity that enables us to be the thinking, knowing, agents that we are occurs outside the brain?

Clark definitely stretches the concept of “outside the brain.” For example, he points to hand waving (those wild gesticulations many of us make while talking) and studies that show that individuals perform more poorly on mental tasks when their ability to gesticulate is limited, or that “the use of spontaneous gesture increases when we are actively thinking a problem through, rather than simply rehearsing a known solution.” But Clark also points to personal devices, like the iPad, which, he argues “transform and extend the reach of bare biological processing in so many ways.”

Clark’s essay is a great read on this concept of embodied cognition. His conclusion, which sounds like it could come straight from the Santa Fe Institute, is that while the brain itself is incredible, “we — the human beings with versatile bodies living in a complex, increasingly technologized, and heavily self-structured, world — are more fantastic still.” And that understanding the mind is more than just understanding the brain.

Good News For Control Freaks!

So screams the first line of a recent article on Science Daily. What’s the good news? A study, published in the journal Nature Neuroscience, shows that “having some authority over how one takes in new information significantly enhances one’s ability to remember it.”

The study compared active and passive learning in a novel way: participants were presented with an array of objects to be memorized, masked by a gray screen. A “viewing window” allowed the study participants to see one object at a time. To test active learning, the participants were able to control the window using a computer mouse. Passive learners viewed a recorded version of the viewing made by an earlier active learner.

The study found significant differences in brain activity in the active and passive learners. Those who had active control over the viewing window were significantly better than their peers at identifying the original objects and their locations.

Cool enough, but to get to a neurological explanation for the phenomenon, the researchers repeated the study with individuals with amnesia (the impaired ability to learn new things) as a result of damage to the hippocampus (the portion of the brain responsible for many memory-related functions). For these participants, there was no difference in recall between active and passive learning.

Additionally, brain imaging of healthy participants indicated that:

Hippocampal activity was highest in the active subjects’ brains during these tests. Several other brain structures were also more engaged when the subject controlled the viewing window, and activity in these brain regions was more synchronized with that of the hippocampus than in the passive trials.

We’re not so sure what to make of the neurological findings in the study, but the clear differences between active and passive learning have lots of relevance for education. It explains why television makes a lousy teaching tool, and why actively engaging students in reading (for example, stopping to ask them questions about what they’ve just read or what they expect to happen next) is helpful for students.

The neural signatures of autism

We recently posted about research at the University of Utah that used MRI to uncover communication deficiencies in the areas responsible for motor control, social functioning, attention, and facial recognition in individuals with autism. The thought is that MRI scans that could identify these deficiencies might serve as a diagnostic tool, thereby enabling earlier and more targeted interventions.

On the heels of that study comes new research from Yale University, published in the Proceedings of the National Academy of Sciences that looked at the neural characteristics of children with autism, their unaffected siblings, and typically developing children. From Science Daily:

The team identified three distinct “neural signatures”: trait markers — brain regions with reduced activity in children with ASD and their unaffected siblings; state markers — brain areas with reduced activity found only in children with autism; and compensatory activity — enhanced activity seen only in unaffected siblings. The enhanced brain activity may reflect a developmental process by which these children overcome a genetic predisposition to develop ASD.

The authors were particularly intrigued by the distinct brain responses exhibited by typically developing children and the unaffected siblings of children with autism because their behavioral profiles are so similar.

Like the authors of the University of Utah study, the Yale researchers are hopeful that the study the study could eventually lead to earlier and more accurate autism diagnosis.

Baseball on the brain

We’ve got Giants fever here at Be Amazing Learning. For the first time since relocating to San Francisco in the 50s, the Giants are World Series Champs! In honor of that accomplishment, we devote today’s post to the intersection of baseball and the brain.

Last week, we posted on the role of the prefrontal cortex in fans’ near-religous devotion to their teams. Today, it’s the neuroscience of hitting.

Steven Small, professor of neurology and psychology at the University of Chicago, is a contributor to Your Brain On Cubs: Inside the Heads of Players and Fans. His research examines the batter-pitcher match-up from the point of view of the neural networks that control if, when and how the batter swings the bat. From a U of C Medical Center press release:

“If the ball leaves the pitcher’s hand at 100 miles per hour,” Small said, “it will take it 0.367 seconds to reach home plate–less than the time between successive heart beats. For elite batters, such as the Cubs’ Alfonso Soriano, such extraordinary skill can only be accomplished by figuring out what the pitcher will do before he even releases the ball.”

Small, an expert on the brain imaging of human behavior, uses functional magnetic resonance imaging (fMRI) to study how the brain of professional athletes plans complex movements, such as swinging a baseball bat. With fMRI, researchers can peer into the brain while an athlete focuses on a video of a real situation, such as a pitcher preparing (e.g., winding up, gripping the ball and then releasing the pitch. The scanner can identify the various parts of the brain that activate as the batter prepares his swing.

In several related studies, Small has found patterns that are common as people learn a new task and then slowly master that skill through practice. Based on this research, it would be expected for a novice baseball player to have more brain activation when preparing to swing a bat than an expert. Experts require less brain power because their brains become more efficient at that task as they gain proficiency.

Professional athletes, he found, activate only the regions of the brain that are critical to a precise activity, such as swinging the bat. The novice, on the other hand, has to activate several other regions, some tangentially connected to the movement and others linked to the neural foundation of emotion.

“When doing something for the first time,” Small said, “there is a lower ability to concentrate and greater involvement of emotion than after gaining expertise. Adding these factors to the brain’s neural programming, makes it more complex and therefore less efficient.”

Congratulations to the World Champion San Francisco Giants! And thanks for the opportunity to veer slightly off topic in celebration of your accomplishment!

Multi-tasking: Can we do it?

Sure. But only up to a point. Our brains can handle two activities, but not three. Which might explain why we have a hard time making decisions when we’re faced with more than two choices.

In the brain, the medial prefrontal cortex (MFC) keeps track of what we’re doing. When we’re working on two tasks, it can divide its attentions, with one half of the region focusing on one task, and the other half on the second task. But, according to researcher Etienne Koechlin of the Universite Pierre et Marie Curie in Paris, we’re actually “divide tasking”, rather than multi-tasking. And things get pretty muddled if we try to add a third task.

Koechlin’s research, “Divided Representation of Concurrent Goals in the Human Frontal Lobes,” was published in the journal Science.

In an interview for Live Science, Koechlin said:

What the results really show is that we can readily divide tasking. We can cook, and at the same time talk on the phone, and switch back and forth between these two activities. However, we cannot multitask with more than two tasks.

Koechlin’s study used fMRI brain scans to monitor 32 subjects as they watch upper case letters on a screen. The subjects had to determine if the letters were presented in the correct order to spell a certain word, such as B-R-A-I-N. They received a monetary reward if they made no errors. As the rewards increased in value, the researchers saw more activity in the MFC.

The subjects were then presented with lower case letters as well, and had to determine if both the upper case and lower case letters spelled a word, B-R-A-I-N and b-r-a-i-n. This required the subjects to switch back and forth between tasks.

During this dual task, the MFC divided up the labor. One hemisphere of the brain encoded the reward associated with the upper case letter task, and so showed activity during that task, while the other region encoded the reward associated with the lower case task.

Essentially, the brain behaved “as if each frontal lobe was pursuing its own goal,” Koechlin said.

When researchers introduced a third letter-matching task, they saw the subject’s accuracy drop considerably. In essence, there was no where for the third task to go.

As for decision-making, Koechlin thinks his results may explain why it’s difficult for us to decide between more than two options:

Previous work has indicated that people like binary choices, or decisions between two things. They have difficulty when decisions involve more than two choices, Koechlin said. When faced with three or more choices, subjects don’t appear to evaluate them rationally; they simply start discarding choices until they get back to a binary choice.
This is perhaps because your brain can’t keep track of the rewards involved with more than two choices, Koechlin said.

If you’re interested in reading more about multi-tasking, check out this episode from NPR’s Talk of the Nation, featuring NPR science correspondent Jon Hamilton and University of Michigan professor Daniel Weissman.